PV Tech’s analysis of the ‘Top Performers’ in PVEL’s ‘2020 PV Module Reliability Scorecard’

The ‘2020 PV Module Reliability Scorecard’ report, undertaken each year by PV Evolution Labs (PVEL) in partnership with DNV GL, has continued to raise questions over key aspects of module reliability. 

This is not just because of the accelerated development and introduction of new modules that drive the LCOE (levelised cost of electricity) down but because well-known and proven reliability testing sequences still catch out products that fail to meet the required degradation rates of less than 2% to become a recognised ‘Top Performer’.
 
Granted, PVEL’s testing sequence criteria has evolved over the years, primarily to increase cycle-times that further pushed the ability of modules to meet the Top Performer requirements as part of the lessons learnt during the evolution in module reliability testing. 

A good example of this would be the PVEL Damp Heat (DH) test, where it has become well known that under the IEC 61215 electrical safety test, a DH duration of only 1,000 hours is required, which led to relatively few modules experiencing electrical safety issues regardless of the Bill of Materials (BOM) used meeting IEC test conditions. 

However, PVEL doubles the number of cycles to 2,000, which has proven to uncover a number of degradation issues that reduce module performance well past the 2% PVEL degradation rule. As such the DH test remains a benchmark for module reliability as the number of BOM variations continue to increase in the pursuit of lower LCOE metrics. 

Importantly, in the 2020 report, PVEL has also added a boron-oxygen (BO) stabilisation step to the tough damp heat testing regime as the test’s high temperature and no current environment can also lead to destabilisation of the passivated BO complexes within some PERC cells, according to PVEL. To further explore this problem, PVEL added a post-DH2000 boron-oxygen stabilisation process to its PQP (Product Qualification Program) sequence.

The more recent introduction of Potential Induced Degradation (PID) testing is another development in line with the mass introduction of Passivated Emitter Rear Cell (PERC) technology that can suffer this type of performance degradation, undermining the performance benefits of the cell technology and therefore the claimed lower LCOE. 

Although PVEL is also introducing a Light and Elevated Temperature Induced Degradation (LeTID) test, this was only announced in mid-2019 and so more time is required for this new test to be introduced, primarily for mono-PERC cells. As a result, the LeTID susceptibility test highlighting Top Performers did not appear in the current report. This was also true for the new backsheet durability sequence. 

In keeping with previous analysis of PVEL’s report we will first look at the four historical reliability tests and the developments noted in the latest report. 

Thermal cycling

In PVEL’s thermal cycling test sequence, modules are placed in an environmental chamber where the temperature is lowered to -40°C, dwelled, then increased to 85°C and dwelled again. Maximum power current is applied to the modules while the temperature is increased and decreased. 

A total of 600 cycles, repeated 200 times over three periods is said to equate to about 84 days in the climate chamber. However, PVEL previously ran the TC test with 600 cycles but had increased this to 800 cycles in recent years. DNV GL had noted in the PV Tech-hosted TechTalk webinar and in the report that the lowered number of cycles was due to its analysis that the TC600 test was actually a sufficient test duration with few reliability excursions being meaningful or could introduce non-representative failure mechanisms when undertaking the extended test. It should be noted that IEC 61215 testing requires only 200 cycles, which has proven insufficient.
  
PVEL had previously noted that thermal cycling performance improved 42% in the 2019 scorecard, even though it used TC800 sequence. 

In the 2020 report, PVEL noted strong results from a host of wafer, cell and module varieties such as standard and half-cut cell module types, as well as thin film, shingled cells, multi-bus bar and heterojunction (HJT) modules.

There were nine PV module manufacturers that achieved Top Performer status in the thermal cycling tests in 2019, compared to 17 manufacturers in the 2020 TC tests. 

It should be noted that both glass-glass and glass-backsheet bifacial modules achieved Top Performer status in the 2020 TC tests and that a total of 54 different modules were recognised as Top Performers. In 2019 the number of Top Performer modules was 24. There were nine PV module manufacturers that achieved Top Performer status in the thermal cycling tests in 2019, compared to 17 manufacturers in the 2020 TC tests. Image: PV Tech

There were nine PV module manufacturers that achieved Top Performer status in the thermal cycling tests in 2019, compared to 17 manufacturers in the 2020 TC tests. Image: PV Tech

Damp heat

In PVEL’s damp heat tests, PV modules are placed in an environmental chamber and held at a constant temperature of 85°C and 85% relative humidity for 2,000 hours (about 84 days in total). The heat and moisture ingress stress the layers of the PV module. In comparison, IEC testing has a duration of only 1,000 hours.

There were six Top Performers in the 2019 damp heat tests, compared to 13 in the 2020 scorecard, a significant increase from previous years.  

PVEL noted that this was mainly due to newer bifacial glass-glass and glass-backsheet module BOM shifting from EVA to POE in glass-glass modules, having performed poorly in previous DH tests. A significant number of tested modules in 2018 and 2019 had exhibited greater than 4% degradation, according to previous PVEL reports. 

As a result, the number of different modules achieving Top Performer status also increased to 32 in the 2020 scorecard, compared to 16 in the 2019 report.There were six Top Performers in the 2019 damp heat tests, compared to 13 in the 2020 scorecard. Image: PV Tech

There were six Top Performers in the 2019 damp heat tests, compared to 13 in the 2020 scorecard. Image: PV Tech

Dynamic mechanical load 

In the DML testing, PVEL installs a module according to the manufacturers’ recommended mounting configuration, then subjected to 1,000 cycles of alternating loading at 1,000 Pa. The module is then placed in an environmental chamber and subjected to 50 thermal cycles (-40°C to 85°C) to cause microcrack propagation, then three sets of 10 humidity freeze cycles (85°C temperature and 85% relative humidity for 20 hours followed by a rapid decrease to -40°C) is used to stimulate potential corrosion.
 
The modules are then characterized and inspected visually to evaluate the status of the module’s frame, edge seal and cell interconnections. The dynamic mechanical loading can induce microcracks that do not necessarily result in significant power loss, according to PVEL, yet  only after thermal cycling and humidity freeze testing that metal conductors affected by cell cracks can break, which leads to black inactive areas and increased power degradation.

DML testing sequence had been tweaked in the 2019 Scorecard to include 30 humidity freeze cycles. About 80% of the historical test data included only 10 humidity freeze cycles, according to PVEL.

As a result, the percentage of dynamic mechanical load sequence Top performers fell by 37% in the 2019 results, versus historical results, according to PVEL. There had been nine PV module manufacturers that had achieved Top Performer status in the 2019 DML tests.
 
However, in the 2020 scorecard that number declined to eight, proving the DML test is proving much more difficult to achieve year-on-year. PVEL put this down to several reasons, including BO destabilisation in PERC cells because of the damp heat conditions during humidity freeze testing.

PVEL also noted that module performance was susceptibility to power loss caused by cell cracking and rapid temperature changes, as part of the new mechanical stress sequence (MSS). PVEL plans to release a separate publication featuring MSS results in the coming months. PVEL also reported that both glass-glass and glass-backsheet bifacial modules had shown similar performance results following the DML sequence. 

A total of 16 different modules had achieved DML Top Performer status in the 2019 scorecard, compared to 19 in the 2020 report. A total of 16 different modules had achieved DML Top Performer status in the 2019 scorecard, compared to 19 in the 2020 report. Image: PV Tech

A total of 16 different modules had achieved DML Top Performer status in the 2019 scorecard, compared to 19 in the 2020 report. Image: PV Tech

Potential-Induced Degradation

PVEL’s PID test is carried out in an environmental chamber with voltage bias equal to the maximum system voltage (MSV) rating of the module (-1000 V or -1500V) being applied under 85°C and 85% relative humidity for two cycles of 96 hours. These temperature, moisture, and voltage bias conditions allow PVEL to evaluate degradation related to increased leakage currents.

Results from the 2019 Scorecard showed 15 PV module manufacturers have PID under control, which was lower than the 20 companies achieving Top Performer status in the 2018 test report. 

The number of PID Top Performers in the 2020 report stood at 20 out of 22 companies reported to have been in the tests that received at least one Top Performer award from the four historical reliability testing regimes. .

Importantly, a total of 47 different modules achieved Top Performer status in the PID tests in 2020 scorecard, compared to 34 different modules in the 2019 report. A total of 47 different modules achieved Top Performer status in the PID tests in 2020 scorecard, compared to 34 different modules in the 2019 report. Image: PV Tech

A total of 47 different modules achieved Top Performer status in the PID tests in 2020 scorecard, compared to 34 different modules in the 2019 report. Image: PV Tech

However, PVEL noted in the latest report that the median PID degradation results had been higher than at any time in its ten years of testing. 

In reference to PID testing of bifacial modules, PVEL noted that there was both a wide range of front-side and rear-side cell degradation, with bias towards higher degradation on the rear side cell. In one case, PVEL reported power loss of over 30%. 

Some of the rear side degradation was said to be due to a reversible polarization effect that could occur in bifacial modules during PID testing, but not all p-type bifacial modules suffered this issue. 

PAN files

New to the Top Performer rankings test is PAN files. This is analysis PVEL has used in its PQP work but is the first time included in benchmarking module energy yields with PVsyst software. 

The procedure is to have three identical PV modules tested across a matrix of operating conditions per IEC 61853-1, ranging in irradiance from 100 W/m2 to 1100 W/m2 and ranging in temperature from 15°C to 75°C. Two 1MW PV plant site simulations are undertaken with one site in a temperate climate at a 0° tilt (in Boston, USA), and a 1 MW site in a desert climate at 20° tilt (in Las Vegas, USA). A custom PAN file is then created with PVsyst’s modelling software that enable PVEL to measure the highest kWh/kWp energy generation based on PVEL’s measurements such as temperature losses and low-light conditions. 

PVEL noted that its historical PAN file data from all PQPs since 2016, meant that only 4% of modules tested would receive a 2020 Scorecard Top Performer designation. 

There are a lot of moving parts in this testing, not least in relation to bifacial modules. The lack of real world data on operating bifacial plus tracker PV power plants has challenged PVsyst modelling accuracy, especially in low-light conditions, according to presentations at the last BiFi workshop in Amsterdam, in September 2019.

PVEL noted that that bifacial modules showed a step-function performance improvement as two thirds of the Top Performers were bifacial modules. The exclusion of inverter clipping at the simulated PV power plant in Las Vegas led to mono-bifacial modules generating 7.7% higher median output higher than monofacial modules. At the simulated horizontal tilt site in Boston the median bifacial energy yield was 3.3% higher than the monofacial median.

Other differentiated yield performances simulated included a heterojunction module, which obviously offered high temperature performance gains, due to having some of the lowest temperature coefficients. 
 
It should be noted that the data presented below is only from PVEL’s PAN testing as part of a PQP where the samples are factory witnessed.

As a result, there were seven 7 PV module manufacturers that achieved Top Performer recognition in the first PAN file test, which included 10 different modules.7 PV module manufacturers that achieved Top Performer recognition in the first PAN file test, which included 10 different modules. Image: PV Tech

7 PV module manufacturers that achieved Top Performer recognition in the first PAN file test, which included 10 different modules. Image: PV Tech

PVEL’s 2020 Top Performers

We should make it clear that in compiling PVEL’s 2020 Top Performer rankings analysis from the historical four key module reliability testing regimes, PVEL has reiterated that not all PV module manufacturers undertaking the scorecard are required to make public the testing results.

Also, it is important to clarify that several PV module manufacturers that achieved Top Performer ratings in some categories, were listed in the 2020 report, yet PVEL had not completed full tests on some of these manufacturer’s modules at the time of the reports publication, which could include some manufacturer’s modules only achieving a few Top Performer rankings but when full testing is completed could have achieved more higher Top Performer rankings. 

The chart below is a compilation of the 22 PV module manufacturers that successfully achieved Top Performer status for any number of modules tested in any of the historical module reliability testing regimes in the 2020 Module Reliability Scorecard that have been made public but may also have not completed all test when PVEL published the report.

Basically, this chart is just the total number of Top Performer rankings a company achieved in the 2020 scorecard, regardless of the number of modules entered the testing by any given module manufacturer.This chart is just the total number of Top Performer rankings a company achieved in the 2020 scorecard, regardless of the number of modules entered the testing by any given module manufacturer. Image: PV Tech

This chart is just the total number of Top Performer rankings a company achieved in the 2020 scorecard, regardless of the number of modules entered the testing by any given module manufacturer. Image: PV Tech

However, the table below also ranks manufacturers by the total number of Top Performer awards, but also breaks out the number of different modules tested from these manufacturers that contributed to each manufacturers total. Top Performers including the number of PV modules tested. Image: PV Tech

Top Performers including the number of PV modules tested. Image: PV Tech 

We can note that the first two manufacturers listed, Astroenergy and LONGi Solar achieved the highest number of Top Performer awards with a contrasting number of modules tested. 

However, further down the rankings PV manufacturers Top Performer awards coupled to the number of different modules receiving awards is more uniform. This indicates that some companies are outperforming others from the perspective of having achieved Top Performer status in all four historic testing regimes, sometimes for just one module but also for several different modules. 

One example of a PV manufacturer achieving Top Performer status in all four historic testing regimes with only one module is REC Group. An example of a PV manufacturer achieving Top Performer status in all four historic testing regimes with more than one module is Silfab. 

Although this is hard to detect in the above combined table, breaking out all the PV manufacturers that achieved Top Performer status in all four historic testing regimes, regardless of the number of different modules tested provides the elite group (see table below) of Top Performers from the 2020 scorecard.There were four manufacturers that achieved this position in the 2020 Scorecard. One more than last year. Image: PV Tech

There were four manufacturers that achieved this position in the 2020 Scorecard. One more than last year. Image: PV Tech

As noted previously, REC Group is represented in this elite group with its monocrystalline PERC-cell based ‘TWIN PEAKS 2’ module, in case people are not that familiar with their module part numbering system. 

LONGi Solar’s HiMO 1 module, which is a mono PERC based module, is also listed as it achieved Top Performer status in all four historic testing regimes.

North American based PV manufacturer, Silfab punched well above its manufacturing weight (capacity) with two mono PERC-based modules achieving Top Performer status in all four historic testing regimes.

Finally, we have China-based Astronergy that had four modules out of six different product offerings receive Top Performer status in all four historic testing regimes. These elite Top Performer modules include Astronergy’s Astro Twins half-cut mono PERC, half module designed product offering. 

The company was also amongst the few manufacturers to achieve Top Performer status in the new PAN file performance analysis. As such, Astronergy has set the bar very high for next year. 

Indeed, PVEL indicated that in the 2020 scorecard testing, several tests, notably DML may have been the toughest test to achieve Top Performer status but there were a number of PV manufacturers modules that were very close to the 2% deviation rule. Therefore, the number of manufacturers with a clean sweep of the historical testing regimes could have been much higher than in previous years. 

That said, the 2021 scorecard should include the planned new testing categories and so in many respects will be a new class of Top Performers from that point onwards. 

The PV Module Reliability Scorecard, now in its 6th edition, ranks commercially available PV modules by their performance in PV Evolution Labs’ Product Qualification Program (PQP), a comprehensive, rigorous test regime that assesses reliability and performance of PV modules. The 2020 rankings will be released on live webinars.

Tristan Erion-Lorico, head of PV module business at PV Evolution Labs (PVEL), will share this year’s top-performing PV modules and discuss key findings from PVEL’s PQP testing, with a special focus on the performance of bifacial PV modules. He will be joined by Dr. Dana Olson, global solar segment leader at DNV GL. Dr. Olson will offer an analysis of trends in PV module quality and discuss how PVEL’s test data is used by DNV GL as part of a module useful life analysis. Mark Osborne of PV Tech will also join the webinar to cover his top highlights from the 2020 Scorecard as compared to the previous editions.

To register for the free to attend ‘PV Tech TechTalk’ webinar, entitled “Top-Performing PV Modules: The 2020 PV Module Reliability Scorecard”, click here.

Webinar timings – local time zones  


Webinar 2 – 
San Francisco (UTC -7): 5/28 at 09:00
New York (UTC -4): 5/28 at 12:00
London (UTC +1): 5/28 at 17:00
Munich (UTC +2): 5/28 at 18:00
Singapore (UTC+8): 5/28 at 24:00

Source: PV Tech

Source: https://www.pv-tech.org/editors-blog/pv-techs-analysis-of-the-top-performers-in-pvels-2020-pv-module-reliability

Posted in PV, Renewables, Solar, Solar PV | Tagged , , , | Leave a comment

The 2020 Global Off-Grid Solar Market Trends Report

February 18, 2020

The 2020 Off-Grid Solar Market Trends is an in-depth analysis on current market dynamics, projections for the coming five years, and a blueprint for how actors in this market can compete in a swiftly evolving industry ecosystem. This year’s edition finds that the industry has made tremendous strides in the past decade in helping developing countries reach their energy access goals, accelerating the global Sustainable Development goal (SDG) 7. To date, more than 180 million off-grid solar units have been sold worldwide and the sector saw $1.5 billion in investments since 2012. The report estimates that the off-grid solar sector currently provides lighting and other energy services to 420 million people. 

Click below to download the full report and summary.

Posted in Off-grid, Solar, Solar PV | Tagged , , , | Leave a comment

SOLAR UNDER STORM SELECT BEST PRACTICES FOR RESILIENT GROUND-MOUNT PV SYSTEMS WITH HURRICANE EXPOSURE – Part 1 of 2

The 2017 hurricane season was one of the most active in history.1 Hurricanes Harvey, Irma, and Maria brought widespread destruction throughout the Caribbean.
In addition to the emotional toll these severe storms had on people in the region, the disruption of critical infrastructure left many communities without such basic services as electricity for prolonged periods of time.

Over the past decades, electricity in the Caribbean has been primarily generated centrally by fuel oil or diesel-fired engines and distributed across the island by overhead lines. However, in recent years, electricity has been supplemented in homes, businesses, industries, government facilities, and utilities by solar photovoltaics (PV). In fact, over half of Caribbean electric utilities already own or operate solar PV as part of their generation mix. Over 225 MW of solar is installed across rooftops, parking canopies, and large tracts of land. Solar PV is the most rapidly growing source of power for many Caribbean islands.2

page8image57169808

Posted in Renewables | Leave a comment

India’s Utility-Scale Solar Parks ‒ A Global Success Story India Is Home to the World’s Largest Utility-Scale Solar Installations

Executive Summary

Renewable energy in India has taken centre stage when it comes to the significant development of energy infrastructure required to achieve India’s economic goals.

In 2016, the Indian government set a target of 175 gigawatts (GW) of renewable energy by financial year (FY) 2021/22 and 275GW by FY2026/27 to transform the power sector from an expensive, unreliable, and polluting fossil fuels-based system into a low-cost, reliable, and low-emission system. In February 2019, the Central Electricity Authority increased the target to 450GW of renewable energy by 2030’.1

So far, India’s electricity sector transition has had a promising start, assisted by lower costs for solar and wind energy generation equipment, cheaper financing, and a favourable policy environment.

In March 2020, India’s on-grid renewable energy capacity stood at 87GW. Of the 30GW of renewable energy capacity installed since the beginning of FY2017/18, coupled with an additional 50GW awarded to date, more than 90% has been contracted at tariffs ranging between Rs2.43-2.80/kilowatt hour (kWh) (~US$35- 40/MWh) with zero indexation for 25 years. This is 60% to70% less than the first- year tariff set for proposed new non-mine mouth coal-fired power plants in India.

page2image57223120

Issues With Ultra Mega Solar Parks

As much as the scale and execution of a large-scale solar park exemplifies India’s technological ingenuity to mobilise capital at scale and at the least cost, it must be acknowledged that it comes with its own set of negative externalities.

Land

Solar parks are land-intensive, and they pose a resource availability challenge for a densely populated country. However, we note the total land required for solar parks is equivalent to the total land required for coal-fired power plants and associated coal mines.

The government should carefully study all options before making plans for new solar parks in future. Wastelands, low-utility non-agricultural land, or reclaimed coal mines should ideally be used for large-scale solar projects.

Labour

The Indian solar construction industry is highly dependent on low-skilled interstate migrant labour and informal employment most of the time. The government could progressively look to execute industry-specific labour reforms for the renewable

26 Mercom India. Gujarat Invites Bids for 950 MW of Projects to be Developed Across Two of its Solar Parks. 25 June 2019.
27 Mercom India, Gujarat Reissues 700 MW from its 1 GW Solar Tender for Dholera Solar Park, 18 March 2020.
28 ET EnergyWorld, NTPC plans 5,000MW ultra-mega solar plant in Kucth worth Rs20,000 crore investment, 20 August 2019.
29 ET EnergyWorld, Gujarat leads India in approved capacity of solar parks, 7 August 2018.page11image59737600

India Is Home to the World’s Largest
Utility-Scale Solar Installations 12

energy industry to reap long-term benefits from the growth industry of the decade.

Grid Stability

Large-scale solar parks are not as easy to operate as decentralised solar systems for grid operators. Large-scale input of power from utility-scale generators is harder for grid stability management from the perspective of the grid operator as it must deal with large voltage and frequency fluctuations because of the intermittent nature of renewables. India’s rooftop solar market has been slower to reach scale in the Indian market, but is finding its feet with more than 5GW of total installed capacity to date.

India has actively looked into various solution to expand its decentralised solar capacity. There have been gigawatt-scale planning and some small installations of floating solar. In addition, government-owned buildings such as offices, hospitals and education facilities are being used to accommodate rooftop solar projects.

India has been growing its grid capacity roughly in step with new generation capacity. India’s grid network successfully managed reduction and consequent increase of 31GW demand within a period of 9 minutes during the recent ‘lights off’ event on 5th April 2020.30 31 This demonstration of grid management supports the argument that with the right planning and additional investment in firming capacity, India’s robust national electricity grid could be further developed to handle large- scale renewable integration.

Conclusion

It is worth looking back over the last four years to see just how far the Indian renewable energy industry has advanced. Indian utility-scale solar parks have been effective in kickstarting India’s energy sector transition. The ultra-mega solar parks have attracted foreign capital as well as top global developers to India, and in return have provided investors with an opportunity to join a US$500-700bn renewable energy and grid infrastructure investment boom in the coming decade.

India’s power industry and the government should make good use of the coronavirus lockdown period to resolve long-standing problems and to be fully prepared for a green infrastructure investment stimulus as India comes out of this pandemic. India should rightly take pride in being able to execute world-leading renewable energy projects and continue to work to resolve short-term policy impediments to achieving its long-term renewable energy aspirations.

The government must also address development-related negative social and economic externalities. It must avoid the mistakes made in the past with large-scale coal mine and thermal power plant development, particularly in terms of development on key agricultural lands and critical forestry reserves.

Posted in Renewables, Solar, Solar Parks, Solar PV | Tagged , , , | Leave a comment

Photovoltaic Module Energy Yield Measurements: Existing Approaches and Best Practice

IEA PVPS Task 13, Subtask 3 Report IEA‐PVPS T13‐11:2018 May 2018

Table of Contents

Foreword …………………………………………………………………………………… 9

Acknowledgements ……………………………………………………………………………….. 10

List of abbreviations ……………………………………………………………………………… 11

Executive Summary ………………………………………………………………. 13

1 2

3 4

Introduction ……………………………………………………………………………………… 17

Background Information ………………………………………………………… 18

  1. 2.1  Scope of Testing………………………………………………………………………………….. 18
  2. 2.2  Energy Yield versus Energy Rating …………………………………………………………. 19

International Survey on Measurement Practices ……………………………………………. 20

Test Environment and Hardware Requirements ……………………………………………….. 22

4.1 Mounting Structure & Surroundings ……………………………………………………. 22

  1. 4.1.1  Mounting rack layout ………………………………………………………………….. 23
  2. 4.1.2  PV module installation ……………………………………………………………… 24
  3. 4.1.3  PV module shading………………………………………………………………………… 24
  4. 4.1.4  Albedo ……………………………………………………………………….. 26
  5. 4.1.5  Sensor positioning ……………………………………………………….. 26

4.2 Current and Voltage Measurements ……………………………………………………. 27

  1. 4.2.1  Hardware solutions …………………………………………………….. 27
  2. 4.2.2  Hardware characteristics and configuration ………………………………….. 30
  3. 4.2.3  Recommendations …………………………………………………………….. 35

4.3 Measurement of Environmental Parameters …………………………………… 37

4.3.1 In‐plane irradiance ………………………………………………………… 37

4.3.2 Module temperature………………………………………………………… 42

4.3.3 Meteorological data ………………………………………………… 45

4.3.4 Spectral irradiance ………………………………………………………. 46

Data Quality Control and Maintenance Practice ………………………………. 50

  1. 5.1  Quality Markers ……………………………………………………………….. 50
  2. 5.2  Maintenance…………………………………………………………………… 50

Characterization of Test Modules ……………………………………………………… 52

  1. 6.1  Module Selection/Sampling………………………………………………………….. 52
  2. 6.2  Pre‐testing and Control Measurements ……………………………………… 53
  3. 7

7.1 Module Energy Yield Benchmarking ……………………………………………………. 55

  1. 7.1.1  Energy yield assessment………………………………………………………………………………. 55
  2. 7.1.2  Impact of STC power …………………………………………………………………………………… 57
  3. 7.1.3  Impact of temperature, irradiance, angle of incidence and spectrum ……………. 59
  4. 7.1.4  Calculation of derate factors ………………………………………………………………. 65
  1. 7.2  Comparison of Module Data from Different Climates……………………………………… 66
  2. 7.3  Module Performance Loss Rates (PLR) …………………………………………………………… 71
    1. 7.3.1  Methodologies …………………………………………………………………………………….. 71
    2. 7.3.2  Performance metrics …………………………………………………………………………… 72
    3. 7.3.3  Filtering and correction techniques ……………………………………………………. 73
    4. 7.3.4  Statistical techniques…………………………………………………………………………. 75

Measurement Uncertainty Analysis …………………………………………………………………………….. 79

  1. 8.1  Introduction ………………………………………………………………………………………………………. 79
  2. 8.2  Methodologies for Uncertainty Analysis ……………………………………………………………….. 80
  3. 8.3  Single Uncertainty Contributions ………………………………………………………………………….. 80
    1. 8.3.1  Uncertainty in STC power UPstc ……………………………………………………………………… 80
    2. 8.3.2  Uncertainty in irradiance Uand irradiation U………………………………………………. 81
    3. 8.3.3  Uncertainty in power UPmax ………………………………………………………………………….. 81
    4. 8.3.4  Uncertainty in key performance indicators UE, UYa and UMPR…………………………….. 82

8

8.4 Relative Uncertainties…………………………………………………………………………………………. 84 Summary and Conclusions …………………………………………………………………………………………. 85 Annex 1: Empty Questionnaire ………………………………………………………………………………………….. 98 Annex 2: Test Facility Sheets ……………………………………………………………………………………………… 99

Foreword

The International Energy Agency (IEA), founded in November 1974, is an autonomous body within the framework of the Organization for Economic Co‐operation and Development (OECD) which car‐ ries out a comprehensive programme of energy co‐operation among its member countries. The European Union also participates in the work of the IEA. Collaboration in research, development and demonstration of new technologies has been an important part of the Agency’s Programme.

The IEA Photovoltaic Power Systems Programme (PVPS) is one of the collaborative R&D Agree‐ ments established within the IEA. Since 1993, the PVPS participants have been conducting a variety of joint projects in the application of photovoltaic conversion of solar energy into electricity.

The mission of the IEA PVPS Technology Collaboration Programme is: To enhance the international collaborative efforts which facilitate the role of photovoltaic solar energy as a cornerstone in the transition to sustainable energy systems. The underlying assumption is that the market for PV sys‐ tems is rapidly expanding to significant penetrations in grid‐connected markets in an increasing number of countries, connected to both the distribution network and the central transmission net‐ work.

This strong market expansion requires the availability of and access to reliable information on the performance and sustainability of PV systems, technical and design guidelines, planning methods, financing, etc., to be shared with the various actors. In particular, the high penetration of PV into main grids requires the development of new grid and PV inverter management strategies, greater focus on solar forecasting and storage, as well as investigations of the economic and technological impact on the whole energy system. New PV business models need to be developed, as the decentralised character of photovoltaics shifts the responsibility for energy generation more into the hands of private owners, municipalities, cities and regions.

IEA PVPS Task 13 engages in focusing the international collaboration in improving the reliability of photovoltaic systems and subsystems by collecting, analyzing and disseminating information on their technical performance and failures, providing a basis for their technical assessment, and de‐ veloping practical recommendations for improving their electrical and economic output.

The current members of the IEA PVPS Task 13 include:

Australia, Austria, Belgium, Canada, China, Denmark, Finland, France, Germany, Israel, Italy, Japan, Malaysia, Netherlands, Norway, SolarPower Europe, Spain, Sweden, Switzerland, Thailand and the United States of America.

This report focusses on the measurement of modules in the field for the purpose of energy yield or performance assessments. This document should help anyone intending to start energy yield meas‐ urements of individual PV modules to obtain a technical insight into the topic, to be able to set‐up his own test facility or to better understand how to interpret results measured by third parties.

The editors of the document are Gabi Friesen and Ulrike Jahn.

The report expresses, as nearly as possible, the international consensus of opinion of the Task 13 experts on the subject dealt with. Further information on the activities and results of the Task can be found at: http://www.iea‐pvps.org.

List of abbreviations

AM Air mass
AoI Angle of incidence
APE Average photon energy
DHI Diffuse horizontal irradiance
DNI Direct normal irradiance
E Energy output
ECT Equivalent cell temperature
ER Energy rating
FF Fill factor
G Irradiance
Gi In‐plane (plane of array) irradiance
Gi,d In‐plane diffuse irradiance
Gi,b In‐plane direct beam irradiance
Geff Effective irradiance or spectrally sensitive irradiance Gstc Reference irradiance at standard test conditions GHI Global horizontal irradiance
GNI Global normal irradiance
H Irradiation
IAM Incident angle modifier
Imp Current at maximum power point
Isc Short circuit current
IR Infrared
KPI Key performance indicator
LID Light induced degradation
MM Spectral mismatch factor
MPP Maximum power point
MPPT Maximum power point tracker
MPR Module performance ratio
Pnom Nominal power
Pmax Power at maximum power point

11

Pstc Power at standard test conditions
Pstc,stab Stabilized power at standard test conditions
PID Potential induced degradation
PLR Performance loss rate
POA Plane of array
PR Performance ratio
Rs Series resistance
Rsc Resistance at short circuit current
Roc Resistance at open circuit voltage
SIF Spectral influence factor
Tstc Reference temperature at standard test conditions Tc Cell temperature
Tamb Ambient temperature
Tmod Module temperature
TBS Back sheet temperature
ΔTCBS Difference between cell and back sheet temperature u Uncertainty
UV Ultraviolet
Vmp Voltage at maximum power point
Voc Open circuit voltage
w Wind speed
Ya PV module (array) energy yield
Yf Final yield
Yr Reference yield
Θ Tilt angle
 Recording interval
γ Pmax temperature coefficient

Executive Summary

The monitoring of single PV modules plays an important role in the demonstration and deeper un‐ derstanding of technological differences in PV module performance, lifetime and failure mecha‐ nisms.

With the growing share and relevance of PV in the market, the number of stakeholders performing outdoor measurements at module level is continuously increasing: test institutes, certification labs, PV module manufacturers, but also non‐experts in the field, e.g. distributors, investors or insurance companies are publishing their results in a wide range of media, from scientific to technical journals, from risk assessment reports to purely commercial publications. The comparability of these meas‐ urements is however made difficult by the different testing approaches and missing declarations on measurement uncertainties. This is mainly due to the fact that there is no dedicated standard or recognized guideline published, covering the specific needs of PV module energy yield measure‐ ments.

The two main reference documents available today are a best practice guideline for the testing of single modules which was presented by DERLAB (European Distributed Energy Resources Labora‐ tories) in 2012 [1] and the IEC 61724‐1 Technical Standard for the monitoring of PV systems, pub‐ lished in 2017 [2]. The first one is limited to the definition of some testing requirements, without distinguishing between different testing purposes. It does not consider uncertainty contributions at single measurement level and gives no recommendations of how to reduce them. The second one addresses many of the missing aspects, with details on sensors, equipment accuracy, quality check and performance analysis, but without considering the special requirements of single module monitoring and benchmarking studies.

Besides the slightly different scopes, the main difference between monitoring at module or system level is that system monitoring generally does not obtain the same accuracy reachable at module level. Secondary effects related to the system configuration (e.g. inverter performance, module sampling, module selection, mismatch losses, …) and spatial variations over the system (e.g. venti‐ lation, soiling, shading, …) are often hiding the technological differences which are the focus and reason for module level monitoring. Moreover, the system monitoring standard does not include any IV‐curve measurements, which are the base of many performance, lifetime and failure studies performed at module level. On the other hand, system monitoring is including some measure‐ ments, which are not relevant for module monitoring like AC currents and voltages or other system related electrical parameters.

Small systems, designed specifically for the purpose of performance or reliability studies, could however be a good alternative if all secondary uncertainties would be reduced to a minimum and the measurements of the DC side and the meteorological parameters would be good enough to allow inter‐comparisons and detailed analysis. The disadvantages of the testing of entire systems are the higher space occupation and the larger number of modules to be characterized and in‐ spected, but, on the other hand, real system stress conditions are better simulated and a more statistically relevant number of modules is measured. New hardware solutions able to measure the IV‐curves of single PV modules within a string could make this approach more attractive and afford‐ able in the near future.

The goal of this document is to fill some of the normative gaps and to help anyone intending to start energy yield measurements of individual PV modules to obtain a technical insight into the topic, to be able to set‐up his own test facility or to better understand how to interpret results measured by third parties.

13

The current practices for energy yield measurements of individual PV modules applied by major international research institutes and test laboratories are presented in this report. Best practice recommendations and suggestions to improve energy yield measurements are given to the reader.

A survey was conducted within the IEA PVPS Task13 consortium to assess how module energy yield measurements are performed today and how the uncertainties are calculated and reported to the end‐users. Fifteen Task members with experience in PV module monitoring from over 30 test facil‐ ities installed all over the world have been interviewed. Many ISO17025 accredited test laborato‐ ries, as well as R&D institutes, have been included. The questionnaire covered all aspects, starting from general questions on the scope of testing to the test equipment, procedures, maintenance practice, data analysis and reporting.

The purposes, for which the monitoring is performed at PV module level, can be manifold:

  •   To assess the stability of a cell technology under specific environmental conditions and stress factors (degradation studies),
  •   to measure the over or under‐performance with respect to a reference technology (benchmarking studies), understanding single environmental loss factors (temperature, spectrum, irradiance, wind, shadows, soiling, etc.) and
  •   to collect data for the validation of energy prediction models or the calibration of PV module parameters for a specific model.It is to be mentioned that module energy yield measurements are also required for the validation of the IEC 61853 standard on energy rating [3,4,5,6], which is currently in elaboration and which aims at replacing the current power rating according to standard test conditions of modules. High precision measurements with accurately determined uncertainties are the key to be able to foster the introduction of any energy rating in the future. Further, energy yield predictions as described in the Report IEA‐PVPS T13‐12:2018 entitled ‘Uncertainties in PV System Yield Predictions and Assessments’ will profit from this.Less frequently, outdoor measurements are performed for the purpose of module characterization, which is mostly done indoors with solar simulators, for which the measurement uncertainties are better defined and known. If characterization is performed under outdoor conditions, it is generally done using a sun‐tracker and other means to control the irradiance and temperature levels. In this case the integrated energy yield is not relevant and the electrical characterization is therefore not within the scope of this document.The different scopes give rise to different testing requirements and data analysis. The most relevant measured or calculated key performance indicators (KPI) are: Instantaneous power (P), energy out‐ put E, energy yield (Ya), module performance ratio (MPR) and performance loss rate (PLR). The measurement accuracy of the output data depends as much on the measurement accuracy of the single components forming the measurement system, as on the conditions at the measurement system and its configuration.This report gives an overview of the most important aspects to be considered for the set‐up of a test facility, e.g. the layout of the test rack and mounting instructions for modules and sensors, as well as how to combine and configure any current/voltage measurement system, like IV‐curve tracers and/or maximum power point trackers (MPPT) for PV modules in order to reduce any measurement artefacts ( e.g transient or capacitive effects, MPP tracking errors, wrong loading, cable losses, …) and errors in the final determination of the KPI’s due to inadeguate data recording (e.g. low sampling rates, syncronisation errors,…).Available quality control measures, such as calibration needs, quality markers for erroneous data (e.g. temperature sensor detachment, sensor soiling, data acqusition errors, …) and maintenance14

practices (visual inspection, cleaning intervals, e‐mail alert, …) are presented to increase the early detection of problems such as drifts, failures or malfunctions, which could further increase the measurement uncertainty.

The final goal is to achieve accurate and reliable data, also over a long time period, and higly comparable data, even with data from other test facilities mounted according to the same guidelines. A better understanding how to reduce single measurement uncertainties, by quantifying and documenting them, is therefore essential.

However, even by reducing all measurement uncertainties, an adequate inter‐comparison between different PV technologies is only possible if the PV modules are selected according to well‐defined sampling procedures and if the STC power and its uncertainty are known. The STC power is actually one of the main contributions to the uncertainty for the calculation of parameters Ya and MPR. The nominal power Pnom as declared by the manufacturer is generally considered as the less adequate for any inter‐comparison, because it can considerably differ from the real power of a PV module, its measurement uncertainty is rarely documented and it is subject to commercial marketing strat‐ egies. The most suitable value for benchmarking of products is the real STC power, with known uncertainty values and no variation after installation. The last aspect is important because, if the module is not stabilized before measuring the STC power, it can lead to misleading results. In gen‐ eral, the lower the measurement uncertainty and the higher the stability in the field, the higher the accuracy of the ranking is. High precision measurements and validated stabilization procedures per‐ formed by accredited test laboratories lead to highest accuracies. In general, electrical characteri‐ zation and optical inspections of PV modules before installation will guarantee that no low quality, defective or damaged modules are chosen.

To understand technological differences and the over‐ or under‐performance of one technology with respect to another under specific climatic conditions, the individual sources of loss with re‐ spect to the power under standard test conditions have to be quantified. Different approaches exist to calculate single de‐rating factors which allow to select the technology with the lowest loss at specific conditions (e.g. high fraction of diffuse light, high temperatures, high angle of incidence, etc.). To calculate the losses, either a full electrical characterization of the module under controlled laboratory conditions or the monitoring of the IV‐curves is needed.

It has to be mentioned that, in terms of bankability of the modules, the degradation rate is more important than the precise knowledge of the instantaneous performance given by the electrical module parameters. In the long term, the annual performance loss can have a higher impact on the life‐time productivity than the electrical parameters. Much less is known on the impact of the en‐ vironment on the ageing process. For this reason, many tests laboratories focus on long‐term meas‐ urement campaigns and the calculation of the PLR.

Independent of the determined KPI, deviations are only meaningful if they are higher than the measurement uncertainties. There are situations, where the magnitude of measurement uncer‐ tainty is larger than the investigated environmental effect so that the result cannot be used for benchmarking or degradation studies without taking it into account. The knowledge and reduction of the uncertainties should be mandatory for anyone performing such measurements. Sometimes, a differentiation has to be done between absolute and relative measurements.

In general, the survey performed within the PVPS Task 13 expert group highlighted that the meas‐ urement accuracy and scientific detail within most test laboratories are very high. This is demon‐ strated by a recurrent use of high precision equipment, good measurement practice and the imple‐ mentation of good quality control and maintenance practice. Nevertheless, the survey revealed some limits, which are mainly the comparability of different outdoor data and the use of these for

15

the validation of models due to a limited harmonization or availability of measurement uncertain‐ ties for the main KPIs. The main reason for this is that compared to the measurement of the STC performance using a solar simulator, for which the measurement uncertainties have been inten‐ sively investigated and validated over the last years, in energy yield measurements the reproduci‐ bility of test conditions is not possible and the determination of the measurement uncertainty is much more complex. The uncertainty is actually site and time dependent and impacted by many factors, which are difficult to estimate and sparely described in literature.

The first step to improve the comparability of outdoor measurements is to agree on the main un‐ certainty contributions and to suggest a common approach for the reporting of measurement un‐ certainties. This document gives recommendations on how to reduce the main uncertainty contri‐ butions and how to calculate them in future projects. Major efforts should be invested in imple‐ menting and validating best practice approaches through international round robins in future.

Posted in PV, Renewables, Solar, Solar PV | Tagged , , , , , , | Leave a comment

Electricity Storage Valuation Framework March 2020 ISBN : 978-92-9260-161-4 Download Assessing system value and ensuring project viability – IRENA Feb 2020

Electricity storage could be a crucial factor in the world’s transition to sustainable energy systems based on renewable sources. Yet electricity markets frequently fail to account properly for the system value of storage.

This report from the International Renewable Energy Agency (IRENA) proposes a five-phase method to assess the value of storage and create viable investment conditions. IRENA’s Electricity Storage Valuation Framework (ESVF) aims to guide storage deployment for the effective integration of solar and wind power.

The three-part report examines storage valuation from different angles:

  • Part 1 outlines the ESVF process for decision makers, regulators and grid operators.
  • Part 2 describes the ESVF methodology in greater detail for experts and modellers.
  • Part 3 presents real-world cases, including examples of cost-effective storage use and maximised service revenues.

Among other findings:

  • Increasing solar and wind penetration brings new challenges for policy makers, regulators and power utilities in terms of system planning and operation.
  • Electricity storage helps to address key technical and economic challenges related to variable renewable energy (VRE) integration.
  • Storage services help to manage the variability and uncertainty that solar and wind use introduce into the power system.
  • By providing multiple services simultaneously, electricity storage permits revenue stacking for greater profitability.
  • Some storage technologies are intrinsically more suited than others for certain services. For instance, batteries provide rapid response to signals, opening the way for new, high-value system services.
  • Electricity storage could accelerate off-grid electrification, enable far higher shares of VRE, and indirectly help to decarbonise the transport sector.
  • Poor accounting for storage value results in so-called “missing money”, with market revenues too low to entice investors.
  • IRENA’s ESVF modelling methodology shows how to overcome the valuation challenge and properly assess the value of electricity storage to the power system.

Posted in Energy Storage, Fuel Cells, Geothermal, Grid Storage, Hydro, PV, Renewables, Solar | Tagged , , , , , , , | Leave a comment

Assessment of Photovoltaic Module Failures in the Field – Study by IEA International Energy Agency

Foreword

The International Energy Agency (IEA), founded in November 1974, is an autonomous body within the framework of the Organization for Economic Co-operation and Development (OECD) which car- ries out a comprehensive programme of energy co-operation among its member countries. The European Union also participates in the work of the IEA. Collaboration in research, development, and demonstration of new technologies has been an important part of the Agency’s Programme.

The IEA Photovoltaic Power Systems Programme (PVPS) is one of the collaborative R&D Agree- ments established within the IEA. Since 1993, the PVPS participants have been conducting a variety of joint projects in the application of photovoltaic conversion of solar energy into electricity.

The mission of the IEA PVPS Technology Collaboration Programme is: To enhance the international collaborative efforts which facilitate the role of photovoltaic solar energy as a cornerstone in the transition to sustainable energy systems. The underlying assumption is that the market for PV sys- tems is rapidly expanding to significant penetrations in grid-connected markets in an increasing number of countries, connected to both the distribution network and the central transmission net- work.

This strong market expansion requires the availability of and access to reliable information on the performance and sustainability of PV systems, technical and design guidelines, planning methods, financing, etc., to be shared with the various actors. In particular, the high penetration of PV into main grids requires the development of new grid and PV inverter management strategies, greater focus on solar forecasting and storage, as well as investigations of the economic and technological impact on the whole energy system. New PV business models need to be developed, as the decen- tralised character of photovoltaics shifts the responsibility for energy generation more into the hands of private owners, municipalities, cities, and regions.

IEA PVPS Task 13 engages in focusing the international collaboration in improving the reliability of photovoltaic systems and subsystems by collecting, analysing and disseminating information on their technical performance and failures, providing a basis for their technical assessment, and de- veloping practical recommendations for improving their electrical and economic output.

The current members of the IEA PVPS Task 13 include:

Australia, Austria, Belgium, China, Denmark, Finland, France, Germany, Israel, Italy, Japan, Malay- sia, Netherlands, Norway, SolarPower Europe, Spain, Sweden, Switzerland, Thailand, and the United States of America.

This report concentrates on the reliability of PV modules. The reliability of PV modules is described by theoretical models. We focus on available models and not in any case on the most important degradation mechanisms. Furthermore, statistical data of the PV module reliability in the field is presented and analysed. The importance of local environmental stressors, such as temperature, humidity, irradiance, wind, etc., influencing the reliability test methods is discussed.

The editors of the document are Marc Köntges, Institute for Solar Energy Research Hamelin, Em- merthal, Germany (DEU), Gernot Oreski, Polymer Competence Center, Leoben, Austria (AUT), and Ulrike Jahn, TÜV Rheinland Energy, Germany.

The report expresses, as much as possible, the international consensus of opinion of the Task 13 experts on the subject dealt with. Further information on the activities and results of the Task can be found at: http://www.iea-pvps.org.



1 Introduction

Currently plenty of PV module failures are known. For investors these failures are difficult to assess because there is little information how much impact and how often a specific failure mode occurs in real world PV systems. The lack of information adds an unnecessary uncertainty to the risk of investment. In this document we try to analyse this problem from three perspectives.

The first perspective is the view of a scientist, PV module expert or manufacturer. In chapter 2 we summarize PV module failure models. These models allow one to analyse the impact of specific well-known degradation modes and failures on the module power with a dependence on weather conditions. These models allow a manufacturer or a PV module expert to evaluate the power loss risk for specific known failures for a specific product. This information can be used to define the warranty criteria for the product. However, most of the failures have not been evaluated to this depth in literature. For these failures, data is summarized from the literature to explain the root cause mechanisms and, if possible, ways to simulate their impact on power production in the fu- ture. A framework is explained to model the power loss of multiple failures.

The second perspective is the view of an investor, banker or underwriter. We collect PV system failure data for four climate zones. These data allow analysing the occurrence of a failure relative to other failure types and its impact on the system power.

Finally, the third perspective is the view of a test institute and PV system planner. Here we explain how one has to modify testing methods for specific failure types to special regions. This allows adapting test methods for a given PV module to specific regional requirements.


page21image47618144

Posted in Manufacturing, PV, Renewables, Solar, Solar PV | Tagged , , , | Leave a comment